Every Data Utility tool in one place: convert JSON, CSV, Parquet and Excel, format, transform, generate, profile, mask and compare data. Free, in your browser.
What Data Utility is
Data Utility is a free, browser-based toolkit with 21 tools for converting, formatting, transforming, generating, profiling, masking and comparing structured data in JSON, CSV, Excel and Parquet. It is used by developers, data engineers, analysts, QA engineers, finance teams and students. There is nothing to install and no account to create.
The Format Converter moves data between JSON, CSV, Parquet and Excel without code or an install. It reads your file in the browser, flattens nested JSON into columns, keeps or guesses column types, and writes the format you choose. Use it to open API data in Excel, load a spreadsheet into an app, shrink a big CSV into Parquet, or look inside a Parquet file. Nothing is uploaded, so it is safe for customer and business data.
The Data Formatter checks and tidies JSON, CSV, XML and YAML. It shows the exact line and column of an error, can fix common JSON mistakes, and cleans CSV by trimming spaces, removing empty rows and columns and dropping duplicates. Developers use it to read API responses, analysts to prepare files before an import. The result can be copied or downloaded, and your text never leaves your device.
The File Compressor shrinks files with gzip in your browser and opens .gz files you receive. Text formats such as CSV, JSON, XML and YAML usually shrink by 70 to 90 percent, which saves storage and speeds up transfers. It handles several files at once and never uploads them, so you can compress logs or exports that contain private data.
Screenshot to Data turns a picture of a table into editable data. It reads the image with OCR in your browser, groups the words into rows and columns, and lets you check the result before you download it as CSV, JSON, Parquet or Excel. Use it for tables in PDFs, reports, slides and chat screenshots. Always compare numbers with the image, because OCR can misread a decimal point.
Merge or Split Files combines many CSV, JSON, Excel or Parquet files into one table, or cuts one big file into many parts. When merging, files are stacked one after another, with an optional source_file column. When splitting, you choose rows per file, a number of equal parts, or one file per value of a column, and download all parts as one ZIP in CSV, JSON, Excel or Parquet. It runs in your browser and nothing is uploaded.
Text to Table turns text you copied into a real table. Paste a table from a web page, a PDF, an email or a chat. The tool finds the layout (tab, comma, semicolon, pipe, spaces, a Markdown table, a key: value list, blocks of Key: value lines that become one row each, or sentences with Key: value parts), moves a currency symbol such as ₹ into the column name so amounts become numbers, makes the first line the header and keeps numbers like 01234 as text. Then download CSV, Excel, JSON or Parquet, or pass it to another tool. Nothing is uploaded.
API Response to Table turns the JSON an API returns into a clean table. Enter the address, add a token if the API needs one, and get one row per record with nested fields flattened into columns such as address.city. Download CSV, Excel, JSON or Parquet, or pass the table to another tool. The request goes from your browser straight to the API, and your token is never saved.
SQL on Your Files lets you query CSV, Excel, JSON and Parquet files with real SQL, without installing a database or a tool like DBeaver. Add one or more files, each becomes a table, then write SELECT, JOIN, GROUP BY, window functions and more. It uses DuckDB, a fast analytics database that runs inside your browser, so your files stay on your device. The SQL engine itself (about 30 MB) is downloaded once from a CDN the first time you run a query.
The JSON Table Editor lets you edit nested JSON without writing code. Open it as a tree to change any value, add or delete keys and items, and change types. Or switch to the Table view, where a list of objects becomes rows and columns (nested fields become columns such as customer.name), and edit cells like a spreadsheet. Every edit updates the JSON, so you can download it again as JSON, or export the table as CSV, Excel or Parquet. You can also open a CSV or Excel file and turn it into JSON; columns named like a.b become nested objects. It all runs in your browser.
Data Transformation lets you reshape a file with a list of steps instead of formulas. Join two files on a key with an inner, left, right or full join, trim spaces, concatenate or split columns, change date formats, change case, find and replace, filter, sort, remove duplicates and fill empty cells. See the result straight away, then download it or send it to another tool. Every step is recorded in Data Lineage.
The SQL Generator turns a CSV, JSON, Excel or Parquet file into CREATE TABLE and INSERT statements for PostgreSQL, MySQL, SQL Server, Oracle or SQLite. It guesses a type for each column, lets you edit names, types, lengths and keys, and writes scripts you can run right away. It is useful for loading spreadsheets into a database and for building test fixtures.
The Data Generator creates realistic fake data: names, emails, phone numbers, addresses, dates, prices and more. Pick a preset or build your own columns, choose up to 500,000 rows, and download CSV, JSON, Parquet or Excel. Developers and testers use it to fill demos, load-test apps and avoid copying real customer data into test systems.
The Synthetic Data Generator learns from your own file and makes new rows that behave like it. Number and date columns keep their range, spread and the way they move together, such as age and salary. Category columns keep their shares. Names, emails, phones and similar fields get new fake values, ids are renumbered, free text gets the same shape without the same words, and rare values are hidden. No real row is copied. It runs in your browser, and a table shows the real and the synthetic numbers side by side so you can check.
The Schema Data Generator builds test data from your own table definition. Paste a CREATE TABLE statement or a JSON Schema and it creates rows that respect each column: the right types and sizes, NOT NULL columns always filled, unique values without repeats, auto-increment ids and allowed values from CHECK rules. Generate up to 500,000 rows and download them in the format you need.
The Data Profiler gives you a quick health check of a file. It shows the type of each column, missing values, duplicates, outliers and basic statistics such as minimum, maximum, mean and the most common values, with flags for likely problems. Analysts use it before cleaning or loading data, to decide what needs fixing. The report can be downloaded with an optional password.
Data Comparison shows exactly what changed between two versions of a file. Pick a key column, or use the first column or the first two columns, and it lists rows that were added, removed or changed, down to the cell. Use it to check an export against last month, to review a data migration, or to find which values a script changed. CSV and Excel are supported.
Data Lineage is a free data lineage tool that records the full history of a file as you work. Transform your data in Data Utility (convert, clean, join, mask, filter, query) and every step is kept: the input file and where it came from, the transformation and its settings, and the output with its row count. Open the graph to inspect any step, then follow any single column: a column lineage table shows what every step did to it, and a personal data check shows whether columns that look personal were masked. Then share the proof: download the result together with a lineage report. The report is a single HTML page, a tree from the input file through each transformation to the result, plus a JSON copy and a SHA-256 checksum of the file. Everything runs and is stored in your browser; nothing is uploaded and no account is needed.
Data Masking hides personal data before you share a file. It detects columns that look like emails, phones, names, addresses and card numbers, suggests a method for each, and previews the result. Choose fake data, partial masking, hashing, noise, rounding or removal. Consistent masking gives the same output for the same input, so related files still line up. Your data stays in your browser.
Chat with Data lets you ask questions about a file in plain English. It uses your own free Gemini key and sends only a summary of your data, such as column names, types and statistics. The numbers in the answers are calculated in your browser, so they are exact. Use it to explore a new dataset, find trends or get a quick answer without writing formulas.
The Data Dictionary Generator writes a CREATE TABLE script with a description for every column. Load a CSV, Excel, JSON or Parquet file, choose your database and it produces documented SQL for PostgreSQL, MySQL, SQL Server, Oracle or SQLite. It uses your own Gemini key and only a summary of the data, and it saves hours of manual documentation.
The Dataset README Generator writes a README.md that explains your data: what it contains, how many rows and columns, and what each column means. It is built from statistics of your file and uses your own Gemini key. Add it to a repository, a shared drive or a data catalog so the next person understands the dataset. Read it once before sharing.
Converter, SQL on Your Files, Data Transformation, Data Profiler, Data Masking and the AI tools read JSON, CSV, TSV, Excel (.xlsx, first sheet) and Parquet. Data Comparison reads CSV and Excel. The Data Formatter handles JSON, CSV, XML and YAML, and the File Compressor writes gzip. Old .xls files are not supported: save them as .xlsx first.
Where your data is processed
File contents are processed in your browser and are not uploaded to Data Utility. Four things use the network: the AI tools send column names, types, statistics and, if you leave the option on, a few sample values to Google Gemini with your own key; API Response to Table makes your browser call the address you enter; Screenshot to Data downloads its OCR engine once; and anonymous usage statistics are collected, never the contents of your files. The Privacy policy has the details.
Because everything runs in your browser, the file size depends on your computer. As a guide, CSV files up to about 100 MB work well, JSON up to about 50 MB, Parquet about 30 MB and Excel about 20 MB. For larger files, use large file mode where it is offered, or split the file first.
Price
Data Utility is free to use, with no sign-up and no advertising.